I believe that AngelList is going to be a HUGE resource for companies to use for recruiting. So I'm going to start leaving some pro-tips here as I learn & navigate the AngelList system. I'll also invite the AL folks to comment directly on this post.
Today, from what I can tell, there are 16,834 candidates on AngelList Talent:
I expect that number to balloon substantially over the coming 12 months.
Stay tuned for pro tips in the comments below. Also feel free to post your own, as well as questions on how we use AngelList at ShareThis for recruiting.
NOTE: The AL Talent system is changing literally daily -- amazing how much development they're doing on it. So many of these things will almost certainly be out of date a few months down the road.
Love this article about how AL is disrupting hiring: http://fitfrnd.com/blog/2014/11/23/silicon-valleys-best-kept-secret-angel-list-slowly-disrupting-hiring-industry/
Here's an important pro tip!!! If you want to search for employees that either currently work or previously worked at a company, do not just type the company name in as a keyword! That makes the search restrictive (if you type two company names in, it'll look only for candidates that have worked at both those companies). Instead, use the "experience" drop-down to choose companies. That'll do an "OR" search instead of an "AND" search.
Here's a baller way to find hot companies on AngelList -- or if you're in recruiting mode, to find the ones that aren't as hot to recruit from. First, go to this advanced search page on AngelList: https://angel.co/companies
And then you can do things like this:
And here is detail on what the "signal" ratio means, and how it's calculated:
"Signal is sort of a measure of how well connected a company/investor is or how good their background is. It's sort of ambiguous, though, because it's a fairly complicated algorithm.
The way it works is that every entity on AngelList is connected to every other entity via the people who are connected to both of them. We use that to seed high values to companies that have had great exits, or schools that are really good, or lots of candidates apply to a particular startup, etc. Then, we calculate a score for everyone else by letting the value flow through the system from those starting points.
So, for example, if an investor was an early investor in Facebook, Google, Linked In, and Twitter, they're closely connected to a number of awesome companies. This makes their score quite high. Then, if they invest in a new startup, that's a signal that the new startup is worth looking into, so the score of the startup goes up. Same thing if one of the founders previously worked at Google or went to MIT, etc."
Aah bummer, AngelList changed its display, so it no longer states how many candidates are on AL. So, I'll no longer be able to report on its growth.
Huh, interesting, it looks like AngelList seeing 16.9% monthly growth in the available candidate pool. When I wrote this blog a month ago, there were 16,834 total candidates. Now, a month later, there are 19,680 total candidates.
At this growth rate, the candidate pool will more than double by the end of 2013. We'll see if it keeps up!
Keywords are EXACT!
I just realized that keyword searches are exact. For example, I get a different results set for "Head Product" and "Head of Product". Hopefully this will change soon, but for right now, it matters exactly how you phrase the keyword search.
AND commas don't seem to matter. For example "Director Product" will return "Director, Product" results.
I asked AL:
When I post 2 skillsets, what does that do? Do you only look for people that match both, to recommend? And what does "recommending" mean? Do you send an email to candidates that match both saying "new job just popped up!" type of thing? Is it geo bounded, so only people in NYC would get that?
To which my POC replied:
"Right now, the only time we promote companies to candidates is when the candidate signs up. There are 3 companies in the welcome email they get under under a header that says 'Jobs in New York'. Companies who's jobs are tagged with the same skills that the candidate tagged themselves with rank higher and are more likely to be in that email. You'll only ever be suggested to candidates who are in the location of your jobs and tagged with the same roles."
And then I asked:
OK so is it additive or restrictive. If I put "sales and marketing" and "advertising" do you restrict to people that have both, or do you show to people that have either?
And he replied:
"We'd show it to people who have either, although people with both get priority."
I asked AL:
"It looks like people that I "send message" to get put into the "yes list" -- is that right?
So am I then better off just hitting "Yes, Get Intro" vs. "Send Message," if the end result of "send message" is just to get an intro? What's the advantage to using "SendMessage"?
Also when I "send message" does the job seeker get an email with my message, or do they have to go to the AL website to see that I've sent a message?
My AngelList POC then replied with this pro-tip:
"Send message does put the candidate in the 'Yes' List. It's better than just clicking Yes because it tells the candidate you've taken the trouble to look through their profile and write a personal note to them. The response rate from candidates when the startup sends a message is significantly higher. Whether you use 'Send Message' or 'Yes, Get Intro', the candidate gets an email telling them you're interested. That email also has a summary of the company, in your case ShareThis, and a link to your profile.
"When you send a message, the message is added to the email we send the candidate notifying them that a startup wants to talk to them. If they reply, you'll see it in the intro email that has you and the candidate cc'ed. There's no way to see the messages you've sent that haven't been replied to, we still need to add that in."
This is the first of a multi-part blog post I'll be writing over the next week that will chronicle my experience raising a $1MM round for AppMakr.
I'll be sharing my learning and experiences as a first-time fundraiser out here in the Valley. My goal is to provide pragmatic tips to help other entrepreneurs understand the process and short-cut the time fundraising typically takes. Think of it as download that condenses 4 months of learning into a series of blogs you can read in an hour.
Be sure to subscribe to the blog if you'd like to get those future posts. Also, we're throwing a party to thank the investors who made this round possible, and celebrating the fact that over 1,000,000 people have now used apps made through AppMakr. RSVP here to join us on 10/28 at 6:30pm. You'll meet Mitch Kapor, George Zachary, Pietro Dova, Ben Narasin and other AppMakr investors.
For this first post, I scored an interview with Naval Ravikant, one of the co-founders of VentureHacks, which runs AngelList. AppMakr went through AngelList, and intros from AngelList were responsible for 54.5% ($545k) of the $1MM we raised. Needless to say, these guys rock. I'd also like to give a huge shout-out to my brother Sam Odio and amazing entrepreneur James Hong, both of whom intro'd me to Nivi & Naval of AngelList at the beginning of our fundraising process.
Here's the video with Naval:
By the title of the post, you might think this about to be some amazingly woven story of how restricting my calories helped me build talent and thus get married. Nope. It's just a post about a few really good books I've read recently.
Good Calories, Bad Calories
Good Calories, Bad Calories, by Gary Taubes is a pro-meat book which covers dietary "history" since the 1950s. What I liked most about it was that it covered three angles simultaneously, the political angle (which, unfortunately, seems to have as much of an impact on our nation's diet as any other angle), the research angle, and the biological angle.